AI/ML NOTES

All of my AI/ML Notes from CombatWombatHub/aiml-notes converted to a public GitHub Pages site with Sphinx Book Theme.

AI/ML:

• Artificial Intelligence (AI)
  • Categories
  • Development
  • Resources
    • GeeksForGeeks
    • Kaggle
    • Machine Learning Mastery
    • 3Blue1Brown
    • DataCamp
  • Portfolio
• Generative AI
• Machine Learning (ML)
  • Categories
  • Supervised Learning
    • Classification
    • Regression
    • Classification|Regression
    • Ensemble Learning
      • Bagging
      • Boosting
      • Stacking
  • Unsupervised Learning
    • Clustering
      • Centroid-Based
      • Distribution-Based
      • Connectivity-Based
      • Density-Based
    • Dimensionality Reduction
    • Association Rule Mining
  • Reinforcement Learning
    • Model-Based
    • Model-Free
  • Forecasting Models
  • Semi-Supervised Learning
  • Self-Supervised Learning
• Natural Language Processing (NLP)
  • Maintenance Records Classification Task
• ML Development
  • Data Preprocessing
  • Exploratory Data Analysis
  • Model Evaluation and Tuning
  • Deploying
• Fundamentals
  • Error
  • Tokenization
    • TF-IDF (Term Frequency - Inverse Document Frequency) Matrix
• Metrics
  • Basics
  • Regression Metrics
  • Classification Metrics

Portfolio:

• DataCamp Notes
  • Extracting DataFrames from DataCamp
• Supervised Learning with scikit-learn
  • Supervised Learning Basics
    • Types
    • Terminology
    • Data Prerequisites
    • scikit-learn Syntax
  • Intro to Classification
    • k-Nearest Neighbors
    • The Churn Dataset
    • Choose Data
    • Fit
    • Predict
    • Measuring Model Performance (train-test-split)
    • Model Complexity (Overfitting/Underfitting)
• Kaggle NLP Absolute Beginners
  • NLP For Classification
  • U.S. Patent Phrase to Phrase Matching Competition
    • Get the Dataset
    • Examine the DataSet
• Machine Learning Mastery Python Mini Course
  • Creating DataFrames
    • Create a simple DataFrame
    • Create DataFrame from CSV URL
  • Examining the Data
    • Describe
    • Scatter Plot Matrix
    • Histogram
    • Box Plot
  • Pre-Processing Data
    • Standardize (Scale and Center)
    • Resampling
    • K-Fold Cross Validation
  • Evaluation Metrics
    • Logloss
    • Confusion Matrix
    • Classification Report
    • RMSE and R-Squared
  • Spot-Check Algorithms
    • Linear Algorithms
    • Non-Linear Algorithms
    • Ensemble Algorithms
  • Model Comparison and Selection
  • Improving Model Accuracy
    • Parameter Tuning
    • Ensemble Predictions
  • Finalize and Save

Sphinx:

• Example Markdown File
  • Sphinx Placeholder
  • Mermaid Example
• Example Jupyter Notebook
  • Python Cell Tests
  • Mermaid Diagrams
• Example reStructuredText File
  • Subtitle